An Improved Eigenvalue-Based Channelized Sub-band Spectrum Detection Method

Abstract

Eigenvalue-based spectrum detection has become a research hot topic, which can make detection by catching correlation features in space and time domains. However, most existing methods only consider part of eigenvalues rather than all the eigenvalues. Motivated by this, this paper focuses on all the eigenvalues of sample covariance matrix in digital channelized system and proposes an improved sub-band spectrum detection method. Utilizing the distribution characteristics of the maximum eigenvalue of covariance matrix and the correlation of all the average eigenvalues, a better theoretical expression of detection threshold is obtained. The proposed method can not only overcome the affection of noise uncertainty, but also achieve high detection probability under low SNR environment. Simulations are performed to verify the effectiveness of the proposed method.